1、查找轮廓随机用不同的颜色画出

import cv2
import numpy as np


def get_contour_colors(num_contours):
    # 定义颜色表 (BGR 格式)
    colors = [
        (255, 0, 0),
        (255, 50, 0),
        (255, 100, 0),
        (255, 150, 0),
        (255, 200, 0),
        (255, 255, 0),
        (200, 255, 0),
        (150, 255, 0),
        (100, 255, 0),
        (50, 255, 0),
        (0, 255, 0),
        (0, 255, 50),
        (0, 255, 100),
        (0, 255, 150),
        (0, 255, 200),
        (0, 255, 255),
        (0, 200, 255),
        (0, 150, 255),
        (0, 100, 255),
        (0, 50, 255),
        (0, 0, 255),
    ]
    # 返回一个颜色表
    return [colors[i % len(colors)] for i in range(num_contours)]


def fill_contours(img, contours):
    # 创建空白的图像，用来画轮廓表
    filled_img = np.zeros_like(img)
    num_contours = len(contours)
    # 颜色表
    colors = get_contour_colors(num_contours)

    for i, contour in enumerate(contours):
        cv2.drawContours(filled_img, [contour], -1, colors[i], -1)

    return filled_img


# 读取原图，原图是RGB图
img = cv2.imread('1.png')
gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)

# 查找轮廓
contours, _ = cv2.findContours(gray, cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_NONE)

# 填充轮廓
filled_img = fill_contours(img, contours)


cv2.imshow('Filled Contours', filled_img)
cv2.waitKey(0)
cv2.destroyAllWindows()

原图：

输出：

2、查找轮廓按大小用不同的颜色画出 

import cv2
import numpy as np



def get_color(k, start_color=(255, 0, 0), end_color=(0, 0, 255)):
    out_color = []   # 输出的颜色
    for i in range(3):
        single_color = int((end_color[i] - start_color[i]) * k + start_color[i])
        out_color.append(single_color)
    for j in range(3):
        if out_color[j] > 255:
            out_color[j] = 255
        elif out_color[j] < 0:
            out_color[j] = 0

    return out_color


def fill_contours(img, contours):
    # 创建空白的图像，用来画轮廓表
    filled_img = np.zeros_like(img)
    # num_contours = len(contours)

    dims = []   # 所有的轮廓的尺寸
    for contour in contours:
        rect = cv2.minAreaRect(contour)  # 获取最小外接矩形
        dia = rect[1][0] if rect[1][0] <= rect[1][1] else rect[1][1]  # 计算轮廓的最短尺寸，并获取直径
        dims.append(dia)
    max_dim = max(dims)  # 最大尺寸
    min_dim = min(dims)  # 最小尺寸
    range_dim = max_dim - min_dim   # 尺寸范围

    for i, contour in enumerate(contours):
        rect = cv2.minAreaRect(contour)  # 获取最小外接矩形
        dia = rect[1][0] if rect[1][0] <= rect[1][1] else rect[1][1]  # 计算轮廓的最短尺寸，并获取直径
        k = (dia - min_dim) / range_dim    # 尺寸比例
        color = get_color(k)    # 获取颜色
        cv2.drawContours(filled_img, [contour], -1, color, -1)

    return filled_img


# 读取原图，原图是RGB图
img = cv2.imread('1.png')
gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)

# 查找轮廓
contours, _ = cv2.findContours(gray, cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_NONE)

# 填充轮廓
filled_img = fill_contours(img, contours)

cv2.imshow('Filled Contours', filled_img)
cv2.waitKey(0)
cv2.destroyAllWindows()

输出：